Back at the computer I could take a look at the data from the trip finally. I guess I am a bit of a data nerd. Probably a result of my job. So in case you care about these things you can read this post otherwise it might be very boring 😉

I was tracking the whole trip with a GPS bike computer (Garmin edge 705). I was most interested in the following: Distance, time, total ascend, calories, heart rate.

So here we go. This first plot shows the travel distance on the different days:

First some explanations: The horizontal lines indicate the average of all days. There are two of them because there were two days which do not really count as full days (“Trondheim” and “North Cape”). These days were just to reach a certain target and not about covering distance like the others. Thus, the black line is including these days and the grey one is excluding them. The blue vertical lines indicate rest days or breaks. The first one was the one week work break at Sunndalsöra and the second was the day on the ship to Bodö.

But now to the data. I did the three longest days by myself (to Kongsberg, over Dovre, to Trondheim) – and also the shortest (to Rondane). It seems that I needed the first days to find the right speed for me. The 186km day (over Dovre) was an exception and only practical because I had a good possibility to sleep there. Beside of that, I find it remarkable how stable the daily distance became when I was travelling with Manuel. That is one of the advantages when cycling with somebody else.

Total distance was 1703 km.

The time in the seat per day was very similar to the distance of course:

Funny thing here is that the days from Lofoten to Alta are even more stable than the distance. And we didn’t even check for the time. Total time was 95 hours.

This next one shows the average speed:

Pretty obvious here is that I was cycling slower alone (first four days). The exception is the 186km-day. But on this day, I had started on 700 meters and was on a weird rush anyway. The last day to the Cape was extremely hilly, which explains the low speed. From Lofoten on, Manuel was pulling me a bit I guess. Or it was a team effect. At least it was not because I pedaled harder, as you can see in the next plot (average heart rate):

I found it interesting that long days seem to correlate with an elevated heart rate, but more about that later. My max heart rate is about 185 by the way. The difference between 105 and 125 is pretty much actually and the overall variation is higher than I expected. It seems that rain leads to a lower heart rate. The days “To Elverum”, “To Koppang”, “Lofoten 2” and “Porsangerfjord” were more or less rainy and had a below average heart rate. That makes sense of course, rainy weather –> less motivation –> lower heart rate.
And here is a fun one:

It looks pretty similar to distance and time of course but it is more even. I needed an average of 3100 kcal per day and it was pretty stable; except the short days and the 6000 kcal on the 186km day. All this added up to 56370 kcal. This corresponds to a calorific content of 10.4 kg Nutella, 108.4 kg apples, 134 liters beer, 469.8 kg iceberg salat, 133.9 Big Macs or (my personal favorite) 6.6 liters of gasoline.

Now something different:

I recalculated the daily ascend in a tracking program and it made it a bit more realistic (I think). Now the total ascend is 10022 m (Before it was more than 16000 m). This plot shows the ascend, normalized on 100 travel kilometers. The short days were combined to “To Trondheim” and “To North Cape” with the respective previous day. A regression line was added and interestingly there is a significant correlation. So there is an average increase of 30 meters of climbing per 100 km, the further you get up to the north (speaking very inaccurately; luckily there is no peer-reviewing of this blog).

And some more statistics:

In the previous plots, it seemed that there was a difference in traveling style for me going alone (white boxes) and together with Manuel (“group”, grey boxes). To check this, I made this overview. First to remark was that the variation for me alone was higher, so in a group, the daily distance and time were more even. Significant differences were found for “time in seat” only (t-test, p<0.05). So I was cycling longer days alone but in the same time, I had the tendency to go slower and for a longer distance (heart rate was similar). I think, this reflects on one hand the different traveling style with a heavy recumbent and a light tourer. But on the other hand, we were not in a hurry in the end and in a group you have somebody to talk to and more reasons to do something else than cycling and sleeping. Conclusion so far, better travel with someone. Thanks to Manuel for being an excellent travel buddy!

And something similar for the influence of rain:

The five rain days (“To Elverum”, “To Koppang”, “Lofoten 2”, “Vesteralen” and “To the north cape”; white boxes) were compared with the non-rain days (grey boxes). But there were no significant differences. Only the lower heart rate on rain days had a lower p-value (0.094) and fits to the earlier assumption that rain decreases the heart rate via reduced motivation. A bigger sample size of rain days would be needed to conclude anything here, but actually I could live without that.

Something complicated for the end:

Correlations between the different data: Pearson correlation coefficients are shown on the top right half of the matrix, including the significance level (red stars) and the respective scatter plot on the lower left half. Data and their distribution is shown in the diagonal. The strongest correlations were found between the obvious: distance, time and calories. More interesting was the correlation between distance and calories to the heart rate. Calories is a bit hard to analyze because I don’t know how it is actually calculated. That leaves the distance. So as assumed earlier, heart rate increases with longer distances. I didn’t realize this before and I wonder why that happens. Of course there could be many reasons. Metabolic or exhaustion effects for example. That is something I want to look up.

Another interesting result were missing correlations: I expected a connection between the normalized ascend and heart rate. But there was nothing. Seems that the heart rate evens out over the day more than I thought. And it is probably a pretty bad indicator how “tough” a day was. Another missing correlation was the one between ascend and speed. There is a weak effect but it seems, similar to the heart rate, to even out through the rest of the day.

Conclusion:

The first six plots were mainly giving an overview over the trip. There was a difference in traveling style when being alone or in a small group. But this didn’t have a significantly effect on the total distance covered each day. The correlation analysis resulted in some expected findings but also provided some surprises. The distance and heart rate correlation was probably the most interesting, together with the absent correlation between ascend to speed and heart rate.

After doing this analysis, I think it was pretty interesting to take a closer look at the data (at least for me). It maybe didn’t give many answers but it helped me to sort my thoughts, summarize the tour and to learn something for the next trip.